code: def _roc_curve_multi(y_true, y_score):
      """Compute micro-average ROC curve"""
      return roc_curve(y_true.ravel(), y_score.ravel())
  
imports: import numpy
  import matplotlib.pyplot
  from sklearn.metrics import roc_curve, auc
  from sklearn.preprocessing import label_binarize
  from ..telemetry import SKLearnEvaluationLogger
  from ..util import is_column_vector, is_row_vector
  from sklearn_evaluation import __version__
  import json
  from pathlib import Path
  from sklearn_evaluation.plot.plot import AbstractPlot, AbstractComposedPlot
  from ploomber_core.exceptions import modify_exceptions
label_desc: Use image node_id 3 for calling a global function with example usage: _roc_curve_multi(y_true, y_score) and returns: roc_curve